DnCNN
Remove Gaussian noise from grayscale images in real‑time.
DnCNN is a 17‑layer denoising convolutional neural network that uses residual learning to remove Gaussian noise (sigma=25) from grayscale images. The network predicts the noise residual and subtracts it from the input to produce a clean image.
Not supported
This model is currently not supported on any IoT chipset.
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View for other chipsetsTechnical Details
Model checkpoint:dncnn_25
Input resolution:256x256
Number of parameters:555K
Model size (float):2.12 MB
Model size (w8a8):581 KB
Applicable Scenarios
- Photography
- Document Scanning
- Medical Imaging
License
Model:MIT
Tags
- real-time
Supported IoT Devices
- Dragonwing IQ-9075 EVK
- Dragonwing IQ-X5121
- Dragonwing IQ-X7181
- Dragonwing Q-6690 MTP
- Dragonwing Q-7790
- Dragonwing Q-8750
- Dragonwing RB3 Gen 2 Vision Kit
- QCS8275 (Proxy)
- QCS8550 (Proxy)
Supported IoT Chipsets
- Qualcomm® QCM6690
- Qualcomm® QCS6490
- Qualcomm® QCS8275 (Proxy)
- Qualcomm® QCS8550 (Proxy)
- Qualcomm® QCS9075
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